If you're a founder dealing with stop doing zero-day ai like this (do this instead), stop what you're doing and read this. Seriously.
Everyone is talking about Zero-Day AI, but 99% of founders are doing it wrong. I learned the hard way so you don't have to.
The Framework That Actually Works
I'm going to share the exact framework I use when evaluating stop doing zero-day ai like this (do this instead). It's not complicated, but it requires discipline.
Step 1: your team matters more than your technology This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the market doesn't care about your roadmap Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly Nothing works perfectly the first time. The companies in my portfolio that nail stop doing zero-day ai like this (do this instead) are the ones that treat it as an ongoing process, not a one-time project.
What I've Learned From 51 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with stop doing zero-day ai like this (do this instead).
The biggest misconception is that you need to the market doesn't care about your roadmap. That's backwards. The companies that win are the ones that customer feedback is the only metric that matters.
I remember sitting with the Anthropic team early on and discussing how they thought about stop doing zero-day ai like this (do this instead). Their approach was counterintuitive but brilliant.
The Counterintuitive Truth
Here's what surprised me most about stop doing zero-day ai like this (do this instead): the best practitioners do less, not more.
When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.
The lesson I took from that experience, and from watching hundreds of other companies, is that the best solutions are often the simplest ones. It sounds simple. It's incredibly hard to execute.
What I Tell Founders
When a founder in my portfolio asks me about stop doing zero-day ai like this (do this instead), I usually start with three questions:
- What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
- What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
- Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around AI threat detection, adversarial AI, AI cybersecurity, AI phishing, zero-day AI that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But here's the thing about stop doing zero-day ai like this (do this instead): you don't need to get everything right on day one. You just need to get started and keep improving.
The founders in my portfolio who excel at stop doing zero-day ai like this (do this instead) share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
Frequently Asked Questions
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.